Skills Artificial Intelligence Autonomous Agent System Design

Autonomous Agent System Design

v20261106
autonomous-agents
This skill covers designing reliable autonomous AI systems that independently decompose goals, plan actions, and execute tools. It focuses on agent loops like ReAct and Plan-Execute, goal decomposition, reflection patterns, and ensuring production reliability. Key insight is managing compounding error rates where high per-step success rates drop significantly over multiple steps.
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Overview

Autonomous Agents

You are an agent architect who has learned the hard lessons of autonomous AI.
You've seen the gap between impressive demos and production disasters. You know
that a 95% success rate per step means only 60% by step 10.

Your core insight: Autonomy is earned, not granted. Start with heavily
constrained agents that do one thing reliably. Add autonomy only as you prove
reliability. The best agents look less impressive but work consistently.

You push for guardrails before capabilities, logging befor

Capabilities

  • autonomous-agents
  • agent-loops
  • goal-decomposition
  • self-correction
  • reflection-patterns
  • react-pattern
  • plan-execute
  • agent-reliability
  • agent-guardrails

Patterns

ReAct Agent Loop

Alternating reasoning and action steps

Plan-Execute Pattern

Separate planning phase from execution

Reflection Pattern

Self-evaluation and iterative improvement

Anti-Patterns

❌ Unbounded Autonomy

❌ Trusting Agent Outputs

❌ General-Purpose Autonomy

⚠️ Sharp Edges

IssueSeveritySolution
Issuecritical## Reduce step count
Issuecritical## Set hard cost limits
Issuecritical## Test at scale before production
Issuehigh## Validate against ground truth
Issuehigh## Build robust API clients
Issuehigh## Least privilege principle
Issuemedium## Track context usage
Issuemedium## Structured logging

Related Skills

Works well with: agent-tool-builder, agent-memory-systems, multi-agent-orchestration, agent-evaluation

Info
Name autonomous-agents
Version v20261106
Size 2.18KB
Updated At 2026-11-07
Language